Topic Modelling and Sentimental Analysis of Students’ Reviews
Source abstract
Abstract
Globally, educational institutions have reported a dramatic shift to online learning in an effort to contain the COVID-19 pandemic. The fundamental concern has been the continuance of education. As a result, several novel solutions have been developed to address technical and pedagogical issues. However, these were not the only difficulties that students faced. The implemented solutions involved the operation of the educational process with less regard for students’ changing circumstances, which obliged them to study from home. Students should be asked to provide a full list of their concerns. As a result, student reflections, including those from Saudi Arabia, have been analysed to identify obstacles encountered during the COVID-19 pandemic. However, most of the analyses relied on closed-ended questions, which limited student involvement. To delve into students’ responses, this study used open-ended questions, a qualitative method (content analysis), a quantitative method (topic modelling), and a sentimental analysis. This study also looked at students’ emotional states during and after the COVID-19 pandemic. In terms of determining trends in students’ input, the results showed that quantitative and qualitative methods produced similar outcomes. Students had unfavourable sentiments about studying during COVID-19 and positive sentiments about the face-to-face study. Furthermore, topic modelling has revealed that the majority of difficulties are more related to the environment (home) and social life. Students were less accepting of online learning. As a result, it is possible to conclude that face-to-face study still attracts students and provides benefits that online study cannot, such as social interaction and effective eye-to-eye communication.
Source: openalex_inverted_index · Quality: baseline
Research context
OpenAlex topics: Sentiment Analysis and Opinion Mining · Public Relations and Crisis Communication
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
References (51)
Show source-provided references
1. Digital response during the COVID-19 pandemic in Saudi Arabia10.2196/19338 ↗
2. E- learning experience of the medical profession’s college students during COVID-19 pandemic in Saudi Arabia10.1186/s12909-021-02860-z ↗
3. COVID-19 and the digital transformation of saudi higher education
4. Saudi university students’ perceptions towards virtual education during COVID-19 pandemic: A case study of language learning via Blackboard10.24093/awej/vol11no3.1 ↗
5. Tracking Saudi EFL students’ reflections of online learning during coronavirus: Different rounds10.3389/feduc.2021.770786 ↗
6. Self-efficacy of Saudi English majors after the emergent transition to online learning and online assessment during the COVID-19 pandemic10.5430/ijhe.v10n3p127 ↗
7. Diagnosis of the effectiveness of the e-learning solutions adopted in Saudi higher education during the COVID-19 pandemic10.1108/OIR-02-2021-0078 ↗
8. The sudden transition to synchronized online learning during the COVID-19 pandemic in Saudi Arabia: A qualitative study exploring medical students’ perspectives10.1186/s12909-020-02208-z ↗
9. How the COVID-19 pandemic is changing education: A perspective from Saudi Arabia
10. N. Razek and S. Coyner, “Cultural impacts on Saudi Students at a Mid-western American University. Counselor Education and Human Services Faculty Publications,” 2013. [Online]. Available: https://ecommons.udayton.edu/edc_fac_pub/4.
11. Reimagining higher education during and post-COVID-19: Challenges and opportunities
12. How the COVID-19 pandemic is reshaping the education service
13. Transitioning to e‐learning during the COVID‐19 pandemic: How have higher education institutions responded to the challenge?10.1007/s10639-021-10633-w ↗
14. Understanding education difficulty during COVID-19 lockdown: Reports on Malaysian university students’ experience10.1109/ACCESS.2020.3029967 ↗
15. Accounting students’ perceptions on e-learning during the COVID--19 pandemic: Preliminary evidence from Saudi Arabia10.35564/jmbe.2020.0015 ↗
16. Distance learning and undergraduate Saudi students’ agency during the COVID-19 pandemic
17. COVID-19 pandemic, outbreak educational sector and students online learning in Saudi Arabia
18. The challenges faced by undergraduate women during the COVID-19 pandemic in Saudi Arabia10.1155/2021/8841997 ↗
19. The impact of the COVID-19 pandemic on the adoption of e-learning among academics in Saudi Arabia
20. Assessing online teaching in higher education amid the COVID-19 pandemic: A case study from Saudi Arabia
21. Academic self-perception and course satisfaction among university students taking virtual classes during the COVID-19 pandemic in the Kingdom of Saudi-Arabia (KSA)10.3390/educsci11030134 ↗
22. Virtual classes during covid 19 pandemic in tertiary level in Saudi Arabia: Challenges and prospects from the students’ perspective
23. Ewing · The Future of Service Post-COVID-19 Pandemic, Volume 1, Rapid Adoption of Digital Service Technology · 2021 · 3710.1007/978-981-33-4126-5_3 ↗
24. Changes that should remain in higher education post COVID-19: A mixed-methods analysis of the experiences at three universities10.18870/hlrc.v11i0.1195 ↗
25. Toward a ‘new normal’ with e-learning in Vietnamese higher education during the post COVID-19 pandemic10.1080/07294360.2020.1823945 ↗
26. Evaluating pre and post covid 19 learning: An empirical study of learners’ perception in higher education10.1007/s10639-021-10521-3 ↗
27. Post-COVID-19 adaptations; the shifts towards online learning, hybrid course delivery and the implications for biosciences courses in the higher education setting10.3389/feduc.2021.711619 ↗
28. Innovation born in isolation: rapid transformation of an in-person medical student radiology elective to a remote learning experience during the COVID-19 pandemic10.1016/j.acra.2020.06.001 ↗
29. Impact of COVID-19 on academic activities and way forward in Indian optometry10.1016/j.optom.2020.06.002 ↗
30. Analyzing open-ended questions by means of text analysis procedures
31. Student’s experiences with online teaching following COVID-19 lockdown: A mixed methods explorative study10.1371/journal.pone.0250378 ↗
32. Lofland · Analyzing social settings: A guide to qualitative observation and analysis · 1995
33. Three approaches to qualitative content analysis10.1177/1049732305276687 ↗
34. L. Grenier, “How to analyze open-ended questions in 5 steps,” Available: http://www.hotjar.com/blog/analyze-open-ended-questions.
35. Sentiment analysis and topic modeling on tweets about online education during COVID-1910.3390/app11188438 ↗
36. Service quality in airport hotel chains through the lens of online reviewers10.1016/j.jretconser.2020.102193 ↗
37. Latent dirichlet allocation
38. Research trends on big data in marketing: A text mining and topic modeling based literature analysis10.1016/j.iedeen.2017.06.002 ↗
39. Sentiment classification of consumer-generated online reviews using topic modeling10.1080/19368623.2017.1310075 ↗
40. An evaluation of airport service experience: An identification of service improvement opportunities based on topic modeling and sentiment analysis
41. A comparative study of utilizing topic models for information retrieval
42. Business intelligence in banking: A literature analysis from 2002 to 2013 using text mining and latent Dirichlet allocation10.1016/j.eswa.2014.09.024 ↗
43. Unfolding the relations between companies and technologies under the Big Data umbrella10.1016/j.compind.2018.03.018 ↗
44. Sharda · Business intelligence, analytics and data science: A managerial perspective · 2017
45. Leveraging Twitter data to understand public sentiment for the COVID-19 outbreak in Singapore10.1016/j.jjimei.2021.100021 ↗
46. Exploring the Ensemble of Classifiers for sentimental analysis - A systematic literature review
47. Social media as a resource for sentiment analysis of Airport Service Quality (ASQ)10.1016/j.jairtraman.2019.01.004 ↗
48. The climate change Twitter dataset10.1016/j.eswa.2022.117541 ↗
49. Using sentiment analysis to reinforce learning: The case of airport community engagement10.1016/j.jairtraman.2022.102228 ↗
50. Analyzing the attitude of Indian citizens during the second wave of COVID-19: A text analytics study10.1016/j.ijdrr.2022.103161 ↗
51. Views of faculty members on the use of e-learning in Saudi medical and health colleges during COVID-19 pandemic